It’s the InDesign Markup Language from Adobe. Adobe defines IDML as an XML-based format for representing InDesign content. IDML effectively allows for backwards compatibility with newer versions of Adobe InDesign. It’s also a great way to back up your file.
Category: Computing & data (Page 64 of 91)
Computing and data is a broad category. Our coverage of computing is largely limited to software, and we are mostly focused on unstructured data, semi-structured data, or mixed data that includes structured data.
Topics include computing platforms, analytics, data science, data modeling, database technologies, machine learning / AI, Internet of Things (IoT), blockchain, augmented reality, bots, programming languages, natural language processing applications such as machine translation, and knowledge graphs.
Related categories: Semantic technologies, Web technologies & information standards, and Internet and platforms.
Microsoft announced the addition of Hindi as the latest language under its Text Analytics service to support businesses and organizations with customer Sentiment Analysis. Text Analytics is part of the Microsoft Azure Cognitive Services. Using this service, organizations can find out what people think of their brand or topic as this enables analyzing Hindi text for clues about positive, neutral, or negative sentiment. The Text Analytics service can be used for any textual/audio input or feedback in combination with Azure Speech-to-Text service. Microsoft’s Text Analytics service uses the latest AI models to analyze content in Hindi, using Natural Language Processing (NLP) for text mining and text analysis. The functionality provided by Text Analytics include sentiment analysis, opinion mining, key phrase extraction, language detection, named entity recognition, and PII detection. Sentiment analysis currently supports more than 20 languages including Hindi.
Microsoft Text Analytics service’s Sentiment Analysis feature evaluates text and returns confidence scores between 0 and 1 for positive, neutral, and negative sentiment for each document and sentences within a document. The service also provides sentiment labels (such as “negative”, “neutral” and “positive”) based on the highest confidence score at a sentence and document-level. It can be accessed from Azure cloud and on-prem using Containers. This helps brands in detecting positive and negative tonality in customer reviews, social media & call center conversations, and forum discussions, among other channels no matter where their data resides.
Related articles:
Google Cloud announced the new Document AI (DocAI) platform, a unified console for document processing. Transforming documents into structured data increases the speed of decision making for companies, unlocking business value and helping develop better experiences for customers. Historically, doing this at scale hasn’t been efficient. DocAI is designed to help businesses use Artificial Intelligence (AI) and machine learning to automate these processes. Today, the DocAI platform is available in preview, enabling you to:
- Ensure your data is accurate and compliant: Automate and validate all your documents to streamline compliance workflows, reduce guesswork, and keep data accurate and compliant.
- Make better business decisions: Improve operational efficiency by extracting structured data from unstructured documents and making that available to your business applications and users.
- Use your data to meet customer expectations: Leverage insights to meet customer expectations and improve CSAT, advocacy, lifetime value, and spend.
With the new DocAI platform, you can access all parsers, tools and solutions (e.g. Lending DocAI, Procurement DocAI) with a unified API, enabling a document solution from evaluation to deployment. It allows creation and customization of document processing workflows. Data extraction is now easier because the specialized parsers on the platform are built with Google Cloud’s predefined taxonomy, without the need to perform additional data mapping or training. General parsers such as OCR (Optical Character Recognition), Form parser, and Document splitter are publicly accessible. You can also request access to specialized parsers such as W9, 1040, W2, 1099-MISC, 1003, invoice, and receipts.
Related articles:
Expert.ai announced and will be presenting an enhanced release of its cloud-based Natural Language API today at API World. The new expert.ai NL API features include:
- Relation extraction to express the connection and accurately answer questions like: “who did what when?”, and “what caused what to whom?”
- Sentiment analysis considering the intrinsic positivity or negativity of the concepts expressed in text, based on the words used (polarity) and how relevant we judge them (intensity)
- A new geographic taxonomy to identify and disambiguate countries and some other administrative divisions (e.g., San Jose, CA, USA vs. San Jose, Costa Rica)
Learn more about expert.ai NL API, now available for free testing, visit and sign up to start developing intelligent applications today.
https://developer.expert.ai, https://expert.ai, https://apiworld.co/
Related articles:
Sentiment analysis (also known as opinion mining or emotion AI) refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.
Sitecore announced Sitecore Artificial Intelligence (AI) Auto Personalization Standard will be available as part of Sitecore Experience Platform 10 (XP) for customers beginning in early 2021. This expands the availability of Sitecore AI and brings quick and simple personalization to customers without requiring an increase in budget or team hours. Sitecore AI Auto Personalization Standard enables users to start personalization right away, without manually defining user segments and with no minimum traffic required, while also:
- Enabling auto personalization, such as images, text snippets and calls to action for sites
- Providing immediate personalization performance visibility with AI analytics embedded in XP
- Tracking critical KPIs, such as engagement value and bounce rates, to measure success
Sitecore also offers Sitecore AI Auto Personalization Premium for customers who want unlimited personalization along with an AI insights dashboard with discovered audiences from both historical and daily data.
Sitecore also announced new content delivery capabilities, coming in early 2021, that will bring additional options for brands, including:
- Sitecore Experience Manager (XM), which will have an added option for customers to leverage a scalable delivery platform for static publishing of Sitecore JSS sites and runtime content delivery for headless sites
- Sitecore Content as a Service (CaaS) capabilities built upon the Sitecore Content Hub SaaS platform, enabling brands to perfect their content strategy with centralized planning and collaboration tools and publish atomic content to a scalable delivery platform through APIs to any channel, on demand.
Related articles:
Automated Machine Learning (AutoML) vendor dotData announced that dotData Stream now supports integration with Amazon SageMaker, a Machine Language Operations Platform (MLOps). Amazon SageMaker is a managed service that provides developers and data scientists with the ability to deploy machine learning (ML) models quickly. Now, with simple point-and-click operations, dotData users can launch dotData Stream on Amazon SageMaker and leverage the platform’s capability to monitor, manage, orchestrate, govern and maintain AI/ML models developed using dotData Platform. This integration provides dotData/AWS users with a full-cycle data science automation experience, from automated AI/ML development using dotData Enterprise through instant AI/ML deployment using dotData Stream to AI/ML lifecycle management with AWS SageMaker. The combination of dotData and Amazon SageMaker helps make AutoML accessible to more enterprises. In July, dotData announced dotData Stream, a portable containerized AI/ML engine that enables real-time predictive capabilities. dotData users can develop AI/ML models using dotData Enterprise or dotData Py and then deploy AI/ML models just with a single docker command using dotData Stream. dotData Stream is designed to be easily deployable on an out of the box MLOps platform or container orchestration frameworks.
Solace announced the general availability of a new version of PubSub+ Event Portal that makes it easier for developers and solution architects to discover, catalog, govern, and visualize Apache Kafka event streams, including those from Confluent and Amazon MSK. Solace first announced these capabilities at Kafka Summit in August and has worked with beta customers to refine functionality and usability. PubSub+ Event Portal gives application teams the ability to:
- Discover and import Apache Kafka events and application interactions;
- Catalog event streams already used within Apache Kafka environments;
- Visualize Apache Kafka topologies;
- Audit to flag discrepancies between design intent and runtime; and,
- Add application and event governance to Apache Kafka data.
PubSub+ Event Portal’s new Kafka-centric capabilities are generally available now.
Subscribe to the Gilbane Advisor
